On A Quest for Combating Filter Bubbles and Misinformation
Summary: Dense subgraph detection identifies echo chambers and misinformation actors; mitigation framed as competitive influence maximization. Examines countermeasures and costs, and ties influence maximization to data-management techniques for mitigation. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Laks V.S. Lakshmanan (University of British Columbia)
BibTeX Citation
@inproceedings{lakshmanan_sigmod22,
title = {{On A Quest for Combating Filter Bubbles and Misinformation}},
author = {Lakshmanan, Laks V.S.},
series = {{SIGMOD} '22},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3514221.3523275},
url = {https://dl.acm.org/doi/10.1145/3514221.3523275},
year = {2022}
}Incoming Citations (Sorted by Pagerank)
Showing 8 of 8 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,916 | Neighborhood-based Hypergraph Core Decomposition | 2023 | VLDB | 6.4474058e-05 |
| 10,226 | Efficient Anchored Densest Subgraph Discovery: Improved Time Complexity and Practical Performance | 2026 | SIGMOD | 5.093636e-05 |
| 10,363 | Efficient and Scalable Directed Densest Subgraph Discovery | 2026 | SIGMOD | 5.093636e-05 |
| 10,528 | Effective Durable Community Search in Large Temporal Graph | 2026 | VLDB | 5.093636e-05 |
| 10,754 | Community Detection in Heterogeneous Information Networks Without Materialization | 2025 | SIGMOD | 5.093636e-05 |
| 10,807 | In-depth Analysis of Densest Subgraph Discovery in a Unified Framework | 2025 | VLDB | 5.093636e-05 |
| 10,930 | Efficient k-Clique Densest Subgraph Discovery: Towards Bridging Practice and Theory | 2025 | VLDB | 5.093636e-05 |
| 11,403 | Mitigating Filter Bubbles Under a Competitive Diffusion Model | 2023 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 0 of 0 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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|---|
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